Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324666
Evan Fakhoury, P. Culmer, B. Henson
A psychophysical magnitude estimation experiment was set up to determine the extent of the contribution of visual feedback during haptic compliance discrimination. Subjects remotely palpated physical compliant samples using a novel pseudo-haptic feedback system which allowed for independent manipulation of visual and haptic feedback. Subjects were asked to rate the compliance of a test sample based on that of a reference sample. While visual feedback was modified by switching the physical test samples shown to participants during indentation, haptic compliance of the test samples was always identical to that of the reference sample. Any variations in haptic sensation was a result of pseudo-haptic illusions. Ratings were collated and fitted to Steven's power law as well as Weber's law. A 0.18 power exponent suggests that the system was successful in generating viscoelastic properties through variations in visual information only. A 19.6% visual change from the reference compliance was necessary in order to perceive a change in haptic compliance using the pseudo-haptic system. These findings could prove beneficial in research and educationalfacilities where advanced force feedback devices are limited or inaccessible, where the concept of pseudo-haptics could be used to simulate various mechanical properties of virtual tissue for training purposes without the needfor complicated or costly force feedback.)
{"title":"The impact of visual cues on haptic compliance discrimination using a pseudo-haptic robotic system","authors":"Evan Fakhoury, P. Culmer, B. Henson","doi":"10.1109/ROBIO.2017.8324666","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324666","url":null,"abstract":"A psychophysical magnitude estimation experiment was set up to determine the extent of the contribution of visual feedback during haptic compliance discrimination. Subjects remotely palpated physical compliant samples using a novel pseudo-haptic feedback system which allowed for independent manipulation of visual and haptic feedback. Subjects were asked to rate the compliance of a test sample based on that of a reference sample. While visual feedback was modified by switching the physical test samples shown to participants during indentation, haptic compliance of the test samples was always identical to that of the reference sample. Any variations in haptic sensation was a result of pseudo-haptic illusions. Ratings were collated and fitted to Steven's power law as well as Weber's law. A 0.18 power exponent suggests that the system was successful in generating viscoelastic properties through variations in visual information only. A 19.6% visual change from the reference compliance was necessary in order to perceive a change in haptic compliance using the pseudo-haptic system. These findings could prove beneficial in research and educationalfacilities where advanced force feedback devices are limited or inaccessible, where the concept of pseudo-haptics could be used to simulate various mechanical properties of virtual tissue for training purposes without the needfor complicated or costly force feedback.)","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133909350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324422
Qing Xu, Jianjun Yuan, Liming Gao, D. Chen
This paper presents a novel obstacle-surmounting robot with eight big wheels, which is designed for searching and rescuing tasks in cities. Four passive planetary swing wheel structures, each of which is composed of two wheels and a planetary structure, are installed into four corners of the vehicle symmetrically. The planet carrier performs as a swing arm to adjust the relative angle of the vehicle' chassis and ground automatically and passively. Consequently, the necessary actuators for the vehicle are reduced to four. For enhancing the stability and adaptability against complex uneven terrain, analysis and simulation experiments have been done to optimize dimensions of the vehicle, where the diameter of the wheel and the central distance of the neighbor planetary sets are modified to 460 mm and 560 mm in the end. Finally, experimental results demonstrate excellent stability and adaptability of the vehicle, and the vehicle is easy to control without any additional operations.
{"title":"Design and simulation analysis of a terrain adaptable wheeled mobile platform","authors":"Qing Xu, Jianjun Yuan, Liming Gao, D. Chen","doi":"10.1109/ROBIO.2017.8324422","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324422","url":null,"abstract":"This paper presents a novel obstacle-surmounting robot with eight big wheels, which is designed for searching and rescuing tasks in cities. Four passive planetary swing wheel structures, each of which is composed of two wheels and a planetary structure, are installed into four corners of the vehicle symmetrically. The planet carrier performs as a swing arm to adjust the relative angle of the vehicle' chassis and ground automatically and passively. Consequently, the necessary actuators for the vehicle are reduced to four. For enhancing the stability and adaptability against complex uneven terrain, analysis and simulation experiments have been done to optimize dimensions of the vehicle, where the diameter of the wheel and the central distance of the neighbor planetary sets are modified to 460 mm and 560 mm in the end. Finally, experimental results demonstrate excellent stability and adaptability of the vehicle, and the vehicle is easy to control without any additional operations.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133675598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324673
Hao Xiong, Xiumin Diao
Keep all cables in tension is crucial for the control of a cable driven parallel manipulator (CDPM). It is challenging to control the tensions in cables of a CDPM with position-controlling actuators because the controlled output positions of actuators are not directly related to cable tensions, especially when cable elasticity is considered. This paper proposes a cable tension control algorithm for fully-constrained CDPMs with positioncontrolling actuators. The proposed tension control algorithm is mathematically derived and verified through simulation using Matlab. Simulation results show that the proposed algorithm can guarantee all cables are in tension for fully-constrained CDPMs with position-controlling actuators, while not affecting the motion control of the CDPM.
{"title":"Cable tension control of cable-driven parallel manipulators with position-controlling actuators","authors":"Hao Xiong, Xiumin Diao","doi":"10.1109/ROBIO.2017.8324673","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324673","url":null,"abstract":"Keep all cables in tension is crucial for the control of a cable driven parallel manipulator (CDPM). It is challenging to control the tensions in cables of a CDPM with position-controlling actuators because the controlled output positions of actuators are not directly related to cable tensions, especially when cable elasticity is considered. This paper proposes a cable tension control algorithm for fully-constrained CDPMs with positioncontrolling actuators. The proposed tension control algorithm is mathematically derived and verified through simulation using Matlab. Simulation results show that the proposed algorithm can guarantee all cables are in tension for fully-constrained CDPMs with position-controlling actuators, while not affecting the motion control of the CDPM.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"30 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116618237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324751
Jing-Chen Hong, Yuta Fukushima, S. Suzuki, Kazuhiro Yasuda, Hiroki Ohashi, H. Iwata
In the previous work, we developed a dorsiflexion support robotic technology (RT) to help with gait rehabilitation for hemiplegic patients. The RT actively supports dorsiflexion force during swing phase with an artificial muscle. Because of the insufficient support of heel rocker, we consider using a spring for assisting resistive dorsiflexion force during loading response phase. The spring can be changed easily on our developed RT, which contributes to advantage of choosing spring with suitable spring constant. Thus, the ultimate goal for us is to find a way to determine the appropriate spring constant for corresponding individual gait to support full heel rocker in loading response phase. Support amount of dorsiflexion torque is needed for determining the spring constant. Therefore, our aim in this paper is to find out the correlation between ankle torque and individual gait factors, such as walking speed and step length. After selecting these factors, we collected gait data for 9 healthy volunteers and derive the formula to estimate dorsiflexion torque using multiple linear regression analysis. An accuracy evaluation test was also done to prove the availability of derived estimation formula.
{"title":"Estimation of ankle dorsiflexion torque during loading response phase for spring coefficient identification","authors":"Jing-Chen Hong, Yuta Fukushima, S. Suzuki, Kazuhiro Yasuda, Hiroki Ohashi, H. Iwata","doi":"10.1109/ROBIO.2017.8324751","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324751","url":null,"abstract":"In the previous work, we developed a dorsiflexion support robotic technology (RT) to help with gait rehabilitation for hemiplegic patients. The RT actively supports dorsiflexion force during swing phase with an artificial muscle. Because of the insufficient support of heel rocker, we consider using a spring for assisting resistive dorsiflexion force during loading response phase. The spring can be changed easily on our developed RT, which contributes to advantage of choosing spring with suitable spring constant. Thus, the ultimate goal for us is to find a way to determine the appropriate spring constant for corresponding individual gait to support full heel rocker in loading response phase. Support amount of dorsiflexion torque is needed for determining the spring constant. Therefore, our aim in this paper is to find out the correlation between ankle torque and individual gait factors, such as walking speed and step length. After selecting these factors, we collected gait data for 9 healthy volunteers and derive the formula to estimate dorsiflexion torque using multiple linear regression analysis. An accuracy evaluation test was also done to prove the availability of derived estimation formula.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115388316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324756
Lingli Yu, Xuanya Shao, Xiaoxin Yan
The autonomous overtaking maneuver is a valuable technology in unmanned vehicle field. However, overtaking is always perplexed by its security and time cost. Now, an autonomous overtaking decision making method based on deep Q-learning network is proposed in this paper, which employs a deep neural network(DNN) to learn Q function from action chosen to state transition. Based on the trained DNN, appropriate action is adopted in different environments for higher reward state. A series of experiments are performed to verify the effectiveness and robustness of our proposed approach for overtaking decision making based on deep Q-learning method. The results support that our approach achieves better security and lower time cost compared with traditional reinforcement learning methods.
{"title":"Autonomous overtaking decision making of driverless bus based on deep Q-learning method","authors":"Lingli Yu, Xuanya Shao, Xiaoxin Yan","doi":"10.1109/ROBIO.2017.8324756","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324756","url":null,"abstract":"The autonomous overtaking maneuver is a valuable technology in unmanned vehicle field. However, overtaking is always perplexed by its security and time cost. Now, an autonomous overtaking decision making method based on deep Q-learning network is proposed in this paper, which employs a deep neural network(DNN) to learn Q function from action chosen to state transition. Based on the trained DNN, appropriate action is adopted in different environments for higher reward state. A series of experiments are performed to verify the effectiveness and robustness of our proposed approach for overtaking decision making based on deep Q-learning method. The results support that our approach achieves better security and lower time cost compared with traditional reinforcement learning methods.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116016075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324578
Jonatan S. Dyrstad, J. R. Mathiassen
We present an approach to robotic deep learning from demonstration in virtual reality, which combines a deep 3D convolutional neural network, for grasp detection from 3D point clouds, with domain randomization to generate a large training data set. The use of virtual reality (VR) enables robot learning from demonstration in a virtual environment. In this environment, a human user can easily and intuitively demonstrate examples of how to grasp an object, such as a fish. From a few dozen of these demonstrations, we use domain randomization to generate a large synthetic training data set consisting of 76 000 example grasps of fish. After training the network using this data set, the network is able to guide a gripper to grasp virtual fish with good success rates. Our domain randomization approach is a step towards an efficient way to perform robotic deep learning from demonstration in virtual reality.
{"title":"Grasping virtual fish: A step towards robotic deep learning from demonstration in virtual reality","authors":"Jonatan S. Dyrstad, J. R. Mathiassen","doi":"10.1109/ROBIO.2017.8324578","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324578","url":null,"abstract":"We present an approach to robotic deep learning from demonstration in virtual reality, which combines a deep 3D convolutional neural network, for grasp detection from 3D point clouds, with domain randomization to generate a large training data set. The use of virtual reality (VR) enables robot learning from demonstration in a virtual environment. In this environment, a human user can easily and intuitively demonstrate examples of how to grasp an object, such as a fish. From a few dozen of these demonstrations, we use domain randomization to generate a large synthetic training data set consisting of 76 000 example grasps of fish. After training the network using this data set, the network is able to guide a gripper to grasp virtual fish with good success rates. Our domain randomization approach is a step towards an efficient way to perform robotic deep learning from demonstration in virtual reality.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"82 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116942461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324543
L. Xue, Yu Xie, Kaiming Zhang, Yanping Chen, Guojun Geng
A teleoperated needle insertion system is an effective way to prevent the physician from repeated X-ray exposures. The process of needle placement is under continuous control of the physician while the patient is kept in remote scanner. Real-time haptic feedback allows the needle insertion to be performed in a safer way and improves performance of surgeons. This paper presents a teleoperated control system with haptic feedback for needle insertion. In our system, a 2 degrees of freedom (DOF) haptic prototype machine is designed for display of the needle insertion force of the tissues to operators during needle insertion. A high-precision displacement platform is used in slave robot to track the displacement of the master robot. Then, we proposed a novel force control framework include two control loops to match the force signals from slave robot to feedback force precisely. The inner loop is a current controller, the outer loop is a force-tracking controller. The effectiveness of the proposed method is verified by experimental results.
{"title":"A haptic force feedback system for teleoperated needle insertion","authors":"L. Xue, Yu Xie, Kaiming Zhang, Yanping Chen, Guojun Geng","doi":"10.1109/ROBIO.2017.8324543","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324543","url":null,"abstract":"A teleoperated needle insertion system is an effective way to prevent the physician from repeated X-ray exposures. The process of needle placement is under continuous control of the physician while the patient is kept in remote scanner. Real-time haptic feedback allows the needle insertion to be performed in a safer way and improves performance of surgeons. This paper presents a teleoperated control system with haptic feedback for needle insertion. In our system, a 2 degrees of freedom (DOF) haptic prototype machine is designed for display of the needle insertion force of the tissues to operators during needle insertion. A high-precision displacement platform is used in slave robot to track the displacement of the master robot. Then, we proposed a novel force control framework include two control loops to match the force signals from slave robot to feedback force precisely. The inner loop is a current controller, the outer loop is a force-tracking controller. The effectiveness of the proposed method is verified by experimental results.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116505560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324476
Adrian Llopart, Ole Ravn, N. Andersen, Jong-Hwan Kim
The end-to-end approach presented in this paper deals with the recognition, detection, segmentation and grasping of objects, assuming no prior knowledge of the environment nor objects. The proposed pipeline is as follows: 1) Usage of a trained Convolutional Neural Net (CNN) that recognizes up to 80 different classes of objects in real time and generates bounding boxes around them. 2) An algorithm to derive in parallel the pointclouds of said regions of interest (ROI). 3) Eight different segmentation methods to remove background data and noise from the pointclouds and obtain a precise result of the semantically segmented objects. 4) Registration of the object's pointclouds over time to generate the best possible model. 5) Utilization of an algorithm to detect an array of grasping positions and orientations based mainly on the geometry of the object's model. 6) Implementation of the system on the humanoid robot MyBot, developed in the RIT Lab at KAIST. 7) An algorithm to find the bounding box of the object's model in 3D to then create a collision object and add it to the octomap. The collision checking between robot's hand and the object is removed to allow grasping using the MoveIt libraries. 8) Selection of the best grasping pose for a certain object, plus execution of the grasping movement. 9) Retrieval of the object and moving it to a desired final position.
{"title":"Generalized framework for the parallel semantic segmentation of multiple objects and posterior manipulation","authors":"Adrian Llopart, Ole Ravn, N. Andersen, Jong-Hwan Kim","doi":"10.1109/ROBIO.2017.8324476","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324476","url":null,"abstract":"The end-to-end approach presented in this paper deals with the recognition, detection, segmentation and grasping of objects, assuming no prior knowledge of the environment nor objects. The proposed pipeline is as follows: 1) Usage of a trained Convolutional Neural Net (CNN) that recognizes up to 80 different classes of objects in real time and generates bounding boxes around them. 2) An algorithm to derive in parallel the pointclouds of said regions of interest (ROI). 3) Eight different segmentation methods to remove background data and noise from the pointclouds and obtain a precise result of the semantically segmented objects. 4) Registration of the object's pointclouds over time to generate the best possible model. 5) Utilization of an algorithm to detect an array of grasping positions and orientations based mainly on the geometry of the object's model. 6) Implementation of the system on the humanoid robot MyBot, developed in the RIT Lab at KAIST. 7) An algorithm to find the bounding box of the object's model in 3D to then create a collision object and add it to the octomap. The collision checking between robot's hand and the object is removed to allow grasping using the MoveIt libraries. 8) Selection of the best grasping pose for a certain object, plus execution of the grasping movement. 9) Retrieval of the object and moving it to a desired final position.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115417411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324759
Tyler H. Ray, J. Kralik
Higher cognitive function was built from a foundation laid by the lowest goal-directed systems in the human brain. Thus, to understand higher cognitive function we must first understand the lowest level. This paper presents our initial results of a computational investigation into the origins of our cognition. We present results from four experiments that investigated the conditions under which initial cognitive abilities arose in our lineage, by comparing a representative chordate, amphioxus, to its close cousins the tunicates and Pikaia. Experiment 1 found that the chordates that would eventually lead to amphioxus and Pikaia evolved a switching mechanism for actions partially from a need to deal with sparse food environments. Experiments 2 & 3 found that predator sensing was the most beneficial adaptation for an organism to receive, followed by increased speed and switching speeds, but also surprisingly, that sensing food was in some cases detrimental. In Experiment 4 we examined the addition of a higher radius of vision and found an amplified performance from predator detection. Our findings show that cognitive adaptations are more advantageous because they enable organisms to avoid predation, eventually enabling them to become predators themselves. Future research will then examine how these basic principles led to more sophisticated cognitive-control mechanisms and learning as evolution progressed to vertebrates, mammals, primates, and ultimately to the complete human mind and brain.
{"title":"Seeking true intelligence from the ground up: Evolutionary origins of cognition","authors":"Tyler H. Ray, J. Kralik","doi":"10.1109/ROBIO.2017.8324759","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324759","url":null,"abstract":"Higher cognitive function was built from a foundation laid by the lowest goal-directed systems in the human brain. Thus, to understand higher cognitive function we must first understand the lowest level. This paper presents our initial results of a computational investigation into the origins of our cognition. We present results from four experiments that investigated the conditions under which initial cognitive abilities arose in our lineage, by comparing a representative chordate, amphioxus, to its close cousins the tunicates and Pikaia. Experiment 1 found that the chordates that would eventually lead to amphioxus and Pikaia evolved a switching mechanism for actions partially from a need to deal with sparse food environments. Experiments 2 & 3 found that predator sensing was the most beneficial adaptation for an organism to receive, followed by increased speed and switching speeds, but also surprisingly, that sensing food was in some cases detrimental. In Experiment 4 we examined the addition of a higher radius of vision and found an amplified performance from predator detection. Our findings show that cognitive adaptations are more advantageous because they enable organisms to avoid predation, eventually enabling them to become predators themselves. Future research will then examine how these basic principles led to more sophisticated cognitive-control mechanisms and learning as evolution progressed to vertebrates, mammals, primates, and ultimately to the complete human mind and brain.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115417155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-12-01DOI: 10.1109/ROBIO.2017.8324669
Jianchao Shi, Jianxun Zhang, Yu Dai, Su He
In order to meet the high precision and real-time demand of master-slave robot, the motion controller of it is designed with field programmable gate array (FPGA) as the core chip. The controller firstly implements real-time Ethernet Powerlink instead of the traditional field bus to transfer location information between master-slave hands, then PID closed-loop control algorithm calculates an pulse width modulation (PWM) duty cycle based on the deviation from the location information of master-slave hands, PWM generation module generates corresponding square wave signal to drive the motor rotates. To feedback actual location information and ensure the security of system, encoder acquisition module and motor enable module are designed with logical hardware in FPGA. Finally the motor position control is realized. The results of experiments show that the motion controller based on FPGA, which is compared with the traditional motion controller realized by digital signal processor (DSP) and FPGA, can greatly improve the precision and real-time performance of master-slave robot.
{"title":"Design of real-time ethernet motion controller based on FPGA","authors":"Jianchao Shi, Jianxun Zhang, Yu Dai, Su He","doi":"10.1109/ROBIO.2017.8324669","DOIUrl":"https://doi.org/10.1109/ROBIO.2017.8324669","url":null,"abstract":"In order to meet the high precision and real-time demand of master-slave robot, the motion controller of it is designed with field programmable gate array (FPGA) as the core chip. The controller firstly implements real-time Ethernet Powerlink instead of the traditional field bus to transfer location information between master-slave hands, then PID closed-loop control algorithm calculates an pulse width modulation (PWM) duty cycle based on the deviation from the location information of master-slave hands, PWM generation module generates corresponding square wave signal to drive the motor rotates. To feedback actual location information and ensure the security of system, encoder acquisition module and motor enable module are designed with logical hardware in FPGA. Finally the motor position control is realized. The results of experiments show that the motion controller based on FPGA, which is compared with the traditional motion controller realized by digital signal processor (DSP) and FPGA, can greatly improve the precision and real-time performance of master-slave robot.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121462245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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